Large institutions often wish to trade in sizes far beyond the liquidity that is instantly available in the market. In today's markets, the best bid or offer quote is usually good for only a few hundred or a few thousand shares. This number or shares is minuscule to institutions that want to trade 100,000 or a million shares. These institutions must carefully choose their trading strategies in order to get good prices on their trades. They face several obstacles:
1. Market Impact                Trading a large number of shares inevitably moves the share price. The art of trading is to complete the trade while minimizing the market impact; this often involves trading the shares slowly over time. Indeed, revealing the intention to trade, such as by posting a public limit order into an ECN (Electronic Communication Network) or a stock exchange, can itself cause market impact by scaring away the other side of the trade.        
2. Front Running                Institutions are justifiably mistrustful that others in the industry will take advantage of their desire to trade through a practice known as “front running.” One example of a classic front running situation is the case in which a broker finds out that a customer wants to buy a large number of shares. Knowing that this purchase interest will increase the share price, the broker buys a number of shares for her or his own account. Alas, this purchasing itself pushes up the price, meaning that the original customer pays a higher price than necessary for the shares.        Other types of front running are more subtle. For example, a trader who sees a large limit order in an ECN to buy at $20 may guess that the stock will soon rise. The trader then puts in an order to buy at $20.01. If the stock rises, the trader makes a profit, and if the stock does not rise, then the trader can sell into the large limit order at $20.        Similarly, a sharp day trader who observes a particular trading pattern may correctly infer that someone is working a large buy order which will push prices up even further. This trader then buys shares, pushing up the price that the original purchaser has to pay to complete the block.        
3. Adverse Selection                No one ever wants to trade with someone who knows more than they do, because they will likely lose in the transaction. An institution that decides to buy a million shares may end up purchasing them from a seller who knows more than they do. This information may originate from within the firm, as in classical insider trading, or the information could be that the other institution wants to sell ten million shares.        
Over the years, a variety of methods have been developed to solve the institutional trading problem:
1. The NYSE Floor                The information environment on the NYSE floor is very complex and generally poorly understood by outsiders. On the NYSE, small orders are handled by computers, but large orders are still negotiated face to face. An institution gives an order to a floor broker, who physically stands at the post on the NYSE where a particular stock is traded. This floor broker interacts on a continuing basis with the other floor brokers and with the NYSE specialist. Hence, the reputation of the floor broker and the specialist are extremely important.        The floor broker will often reveal bits and pieces of information to the floor IF he or she thinks that it will help fill the order at a better price. The floor broker with a large order will talk with others in the crowd and with the specialist to find out if other brokers are working large orders. Often the specialist will point out to a buyer that another floor broker is representing a seller and the two floor brokers will negotiate the trade face to face. The advantage of this method is that only serious buyers and sellers find out about the desire to trade, reducing information leakage and thus market impact.        
2. “Upstairs” Market                In the so-called “upstairs” market, an institution gives the order to a brokerage firm with experience in trading blocks. In the classic approach, the broker then calls natural counter parties. For example, if a buyer wants to purchase 1 million shares, the block broker will first contact its other clients that have been recent sellers and see if they want to sell some more. The broker will also examine institutional holdings and look for holders that have been reducing their stakes. A skilled block broker can thus find the natural counter party to the trade without spilling the trading information to the whole world.        
3. ECNs                Unlike the NYSE floor, ECNs offer speed and anonymity. However, the transparency of ECNs deters investors from placing very large orders into them. Displaying a large order just invites front running behavior from traders who are watching the book. Even if the other traders don't actively front run, displaying a large order may spook the other side of the trade into withdrawing and waiting for a better price.        ECNs often allow “reserve” or hidden orders that are not displayed in the ECN book as one solution to the excess transparency problem. However, this is not a complete solution to the block trading problem.        
4. Basket Trading                Because one of the main risks to traders is that the other side knows more than they do, traders often attempt to prove that they have no information about a particular stock. One way to do this is to trade an entire portfolio. Thus, a mutual fund that has experienced a fund outflow may want to sell an entire basket of stocks. A block trader such as the equity trading desk at Goldman or Merrill may bid aggressively to purchase the entire basket, knowing that the seller has no special information about where the stocks are going.        
5. “Slice and Dice” Trading                The opposite of the basket/block approach is the “Slice and Dice” approach. Given the problems with market impact, one of the obvious ways to reduce impact is to break the order up into smaller pieces and then make a number of small trades. Trading software today makes it easy to break up an order and drip it continuously into the market. Smart order routers opportunistically move orders to whatever venue has liquidity at the moment.        “Slice and Dice” trading has become very popular in recent years because many institutions evaluate the performance of their trading desks against a VWAP (Value Weighted Average Price) benchmark. A trader who breaks up the order and continuously drips or sprays it into the marketplace will come pretty close to the VWAP benchmark.        
6. POSIT                ITG, Inc. operates the POSIT matching system. In the POSIT system, investors place anonymous and secret orders into a matching system that conducts periodic matches during the trading day. If a match is found, the trade is crossed at the midpoint of the bid-ask spread. ITG also acts as an agency broker for institutions, helping them to work the residuals that don't match in POSIT, and they also provide a variety of trading tools. In addition, ITG's TriAct system also allows incoming order flow to interact against the orders they are holding on their way to market.        
7. Liquidnet                Liquidnet operates a Napster-like system in which the LiquidNet software operates on the order management software of large buy-side institutions. The LiquidNet software acts like a trusted spy and talks to the other LiquidNet processes running at other institutions. When it finds a matching order, a little chat box pops up only on the screens of the two matching entities so that they can anonymously negotiate the trade. Only the two natural counter parties ever find out about the trading interest of the other side.        
8. NYFIX Millennium                NYFIX started off as a back office technology provider, transmitting order flow to other trading platforms. However, they were carrying so much order flow that they now offer firms the ability to trade against that order flow.        
None of these methods, however, provide a complete solution to the institutional trading problem. Accordingly, there is a need in the art for a system and method that improves price discovery and reduces slippage associated with trading large orders of financial instruments such as equities.